Marketing is the art of reaching the right people with the right messages at the right time. Since marketers generally cannot afford to craft unique messages for each individual target customer, they deal with large segments of each of their target markets at a time. Clustering is often used to help the marketers determine the desirable segments of customers for target marketing. While clustering can assign each individual customer to a specific cluster, it is useful for the marketers to find a set of customer attributes that uniquely identify one particular cluster of individuals from the other clusters of individuals, so that the marketers can use these customer attributes to target other individuals who also satisfy or possess these customer attributes. These attributes can also be used to identify good candidates for a particular goal (e.g., product purchase) among people who have not yet done the activity that measures the success of the marketer's goal.
The human brain has difficulty visualizing multi-dimensional data, especially when the number of dimensions exceeds five (three spatial, one color, and one size). One common method of displaying a visualization of clustering data is to project the data onto a three-dimensional map and use the spatial relationships to show the similarity among the individual clusters. While this method helps the marketers understand which clusters are most similar to which other clusters, this method of visualization generally does not enable the marketers to readily identify which customer attributes best differentiate each individual cluster from all other clusters.